Summary/Abstract

Canine distemper is an important infectious disease that affects many mammal species. There is evidence of CDV infection in all terrestrial carnivores families and some marine carnivore families. CDV has been detected in wild animal species such as the African lion and Amur tigers and has been responsible for substantial population declines of the animals during outbreaks. First seen in domestic dogs in the late 1970’s, CDV spread through the population rapidly (???). CDV is seen most commonly in domestic cats and dogs but frequent cross species transmission does occur in non-domestic carnivores. In domestic ferrets mortality rates can reach 100%. CDV has been responsible for population declines of endangered mustelids like the black-footed ferret. CDV is also endemic in the eastern U.S. raccoon population. Raccoons are thought to be a reservoir for other wild animals and domestic dogs as well as other species of carnivores. CDV has been found to be persisting in areas like Yellow Stone national park, which has a diverse carnivore population. Multiple outbreaks have occurred in the wolf, coyote and cougar populations Although raccoons are thought to be a major reservoir for CDV, little research has been done to identify the disease dynamics within this population.

Introduction

Canine distemper is an important infectious disease that affects many mammal species. The causative agent, canine distemper virus (CDV) is an enveloped, single stranded, negative sense RNA virus in the Morbillivirus family. Transmitted via the respiratory route, CDV is highly infectious (Deem, Spelman, Yates, & Montali, 2000). There is evidence of CDV infection in all terrestrial carnivores families and some marine carnivore families (Deem et al., 2000). Morbidity and mortality varies depending on the species but closely resembles rabies in wild carnivores (Hoff, Bigler, Proctor, & Stallings, 1974). The Mustelidae family is among the species with the highest fatality rate, while the domestic dog can be a asymptomatic carrier (Deem et al., 2000). CDV has been detected in wild animal species such as the African lion and Amur tigers and has been responsible for substantial population declines of the animals during outbreaks (Roelke-Parker et al., 1996; Seimon et al., 2013).

Canine Distemper Virus In the U.S.

First seen in domestic dogs in the late 1970’s, CDV spread through the population rapidly (Alison et al 2013). CDV is seen most commonly in domestic cats and dogs but frequent cross species transmission does occur in non-domestic carnivores (Allison et al 2013 and (Greene & Appel, 1990). Severity in domestic dogs depends on the animals’ immune status and age in addition to strain virulence (Beineke, Baumgärtner, & Wohlsein, 2015). In the U.S. raccoons (Procyon lotor), foxes (Vulpes vulpes and Urocyon cinereoargenteus), coyotes (Canis latrans), wolves (Canis lupus) , skunks (Mephitis mephitis), badgers (Taxidea taxus), mink (Mustela vison) and ferrets (mustelidae spp.) are among the species susceptible to CDV infection (Kapil et al., 2008; Williams, Thorne, Appel, & Belitsky, 1988). In domestic ferrets mortality rates can reach 100%. CDV has been responsible for population declines of endangered mustelids like the black-footed ferret. CDV is also endemic in the eastern U.S. raccoon population. Raccoons are thought to be a reservoir for other wild animals and domestic dogs as well as other species of carnivores (Alison et al 2013, and (Roscoe, 1993). CDV has been found to be persisting in areas like Yellow Stone national park, which has a diverse carnivore population. Multiple outbreaks have occurred in the wolf, coyote and cougar populations (Almberg, Cross, & Smith, 2010; Almberg, Mech, Smith, Sheldon, & Crabtree, 2009). Although raccoons are thought to be a major reservoir for CDV, little research has been done to identify the disease dynamics within this population. Available data is sparse, dated and focuses on individual states and discrete sites. The use of past and current presence only cases allows for spatio-temporal analysis of the CDV in the southeastern United States. The objective of this study was to identify spatial and temporal patters in distemper virus cases reported to the Southeastern Cooperative Wildlife Disease Study from 1975 to 2013.

Description of data and data source

Data was recorded from Canine distemper positive cases submitted to the Southeastern Cooperative Wildlife Disease Study between 1975 and 2013. Cases were identified as CDV by fluorescent antibody testing and/or histologic diagnosis of characteristic lesions. Species, date of submission, county of origin, and sex were noted. A total number of 701 positive cases were submitted from 13 states over the 38-year period. Positive cases were comprised of raccoons (n=462), gray foxes (n=211), striped skunks (n=13), coyotes (n=7), red foxes (n=3), gray wolves (n=3), one mink and a black bear.

Census and county land area data for Geogia was accessed and downloaded from census.gov.

Species frequency Table
Species n
Black Bear 1
Coyote 7
Gray Fox 211
Gray wolf 3
Mink 1
Raccoon 462
Red Fox 3
Striped Skunk 13

Questions to be addressed

1.Are there temporal trends in cases diagnosed related to the ecology of the hosts?

2.Are there patterns in the timing of species being diagnosed suggesting cross species infection? (raccoons are considered primary reservoirs, are peaks in raccoon infection followed by other species peaks suggesting spillover)

3.Are there spatial patterns of infection within the southeast relating to landuse?

Methods

Data aquisition

Data of animals brought to SCWDS between 1975 and 2013, which were diagnosed as having CDV at post mortem. Cases were identified as CDV by fluorescent antibody testing and/or histologic diagnosis of characteristic lesions. Species, date of submission, county of origin, and sex were noted.

Overview of Data

CDV case data contained the follwing variables; Case number, State, county, area, Sex, Species, Age and collection year. Additional data incluing specific collection dates was also used from a seperate spread sheet for the time series analysis.

Data import and cleaning

Data was imported into R Studio and cleaned to correct data entry errors and missing data. Detailed description of data analysis and cleaning is contained in the processing scripts within the project repository in the processing_code subfolder.

Time Series analsys

time series analysis and ARIMA model construction was conducted using the “fpp2” package from Forecasting: principles and practice, Hyndman & Athanasopoulos.(Hyndman & Athanasopoulos, 2018)

Results

Data Exploration

Number of cases of CDV per state, submitted to SCWDS, 1075-2013

Number of cases of CDV per state, submitted to SCWDS, 1075-2013

Map of CDV cases per state submitted to SCWDS, 1975-2013 .

Map of CDV cases per state submitted to SCWDS, 1975-2013 .

Number of CDV cases per species submitted to SCWDS, 1975-2013

Number of CDV cases per species submitted to SCWDS, 1975-2013

Total Cases per Year, 1975-2013

Total Cases per Year, 1975-2013

Initial probing of the data set revealed the vast majority of cases to be submitted from the state of Georgia. This is understandable as SCWDS is located in Athens, GA. The other feature is that almost all of the submitted cases are Raccoons or Gray Foxes. From this point, data exploration and analysis will focus only on Gray foxes and Raccoons in the state of Georgia as this compromises the majority of cases.

Bivariate analysis of Species and Age of CDV cases submitted to SCWDS, 1975-2013

Bivariate analysis of Species and Age of CDV cases submitted to SCWDS, 1975-2013

The age data is difficult to use as it is a particularly subjective measure in this case and there would need to be very marked changes for anything to be suggested.

Bivariate analysis of Species and Sex of CDV cases submitted to SCWDS, 1975-2013

Bivariate analysis of Species and Sex of CDV cases submitted to SCWDS, 1975-2013

There did not appear to be any clear diff

Raccoon and Gray Fox cases in Georgia presented to SCWDS, 1975-2013

Raccoon and Gray Fox cases in Georgia presented to SCWDS, 1975-2013

Raccoon and Gray Fox cases per breeeding season adjusted

Raccoon and Gray Fox cases per breeeding season adjusted

##Spatial Mapping of Georgia Data

Further qualitative analysis was conducted by mapping disease presence over time at county level.

County Presence over Time of CDV, from cases submitted to SCWDS, 1975-2013

This was further analysed by comparing this distribution of cases over time by splitting cases by species.

Cases of CDV in Gray Foxes and Raccoons in Georgia counties, from cases submitted to SCWDS, 1975-2013

Quantative analysis of the level of clustering of cases was done using Ripley’s K analysis.

Ripley's K analysis of CDV cases in Raccoons and Gray Foxes in Georgia, from cases submitted to SCWDs, 1975-2013

Ripley’s K analysis of CDV cases in Raccoons and Gray Foxes in Georgia, from cases submitted to SCWDs, 1975-2013

Raccoon and Gray Fox cases in Georgia presented to SCWDS, 1975-2013, and human population density

Raccoon and Gray Fox cases in Georgia presented to SCWDS, 1975-2013, and human population density

Raccoon and Gray Fox cases per spm against human population density

Raccoon and Gray Fox cases per spm against human population density

Cases of Raccoons and Gray Foxes were plotted both on a map showing population density per county and a regression of ocervall cases per area for each county against population density per sqm, which suggests a hump shaped relationship.

Time series analysis

Time series analysis was conducted on the number of cases in Gray foxes and Raccoons for the whole state of Georgia in the period 1975-2013 and ARIMA models using lagged predictors constructed using the “fpp2” package from Forecating: principles and practice, Hyndman & Athanasopoulos.(Hyndman & Athanasopoulos, 2018)

Predictive Model

The general model for predicting number of Gray Fox cases using an auto-regression model found using the previous months predictive error along with this months Racoon cases as the most accurate model for prediction.

Gray Fox Prediction General Model

Gray Fox Prediction General Model

Gray Fox Prediction Model

Gray Fox Prediction Model

The process was repeated for predicting Raccoon cases with the strongest model using the previous months Raccoon cases and predictve error in additon to the previous three months Gray Fox numbers.

Raccoon Prediction General Model

Raccoon Prediction General Model

Raccoon Prediction Model

Raccoon Prediction Model

The first model, which uses the number of Raccoon cases from the previous month along with the predictive error for Gray Fox cases from the previous month to predict Gray Fox cases in the current month is the more accurate model with an RMSe of 0.2942214. The second model predicts the current months Raccoon cases using the previous months Raccoon data and model errot in addiiton to Gray Fox cases from the previous three months. Whilst this model was still quite accurate at predicting the number of cases it had a slighlty higher RMSe at 0.5596792.

Discussion

Initial introduction of CDV into wild carnivores in the U.S. in 1960’s was through grey foxes and subsequent spread to raccoons. (Hoff et al., 1974). Outbreak in Raccoons in Berlin, Germany appears to have originated in foxes with transmission seeming to readily occur between the species. (Rentería-Solís et al., 2014)

The analysis of the CDV case data in Raccoons and Gray Foxes suggests a relationship between cases in the two species, with the ARIMA model produced for Gray Fox cases suggesting that monthly case numbers in Gray Foxes can quite accurately be predicted using the previous months Gray Fox error data and the number of Raccoon cases from this month. A second model for the prediction of Raccoon cases using the previous months raccoon data in addition to Gray Fox cases from the previous three months was also quite accurate at predicting Raccoon cases, albeit it had a slightly higher error than the other model.

The spatial analysis of the data showed significant clustering of cases, which is in line with the ecology of the virus which tends to have epizootics where it spreads quickly amongst nearby susceptible. The primary mode of CDV infection is aerosol inhalation, suggesting habitat overlap and contact (Hoff et al., 1974). There appeared to be a much greater number of cases in the northern part of the state. Again the possible reasons for this are diverse; reporting bias due to a range of possible reasons; as the northern part of the state is more densely populated by humans, closer proximity to SCWDS, more suitable habitat and a consequently greater population of susceptible raccoons and gray foxes. Interestingly, there may be a parabolic relationship between population density and number of cases, with very high densities and very low densities having lower number of cases. This suggests that suburban areas may be a hotspot for disease circulation with these areas being attractive to Raccoons particlualry due to the balance of available habitat and easy scavenging opportunites. This is of particualr relevance as the disease is suggested to spillback from raccoons into dogs (Kapil & Yeary, 2011).

The data suggests a correlation between breeding season and the number of cases reported, with positives more likely to occur during the breeding season. This could be due to a number of reasons; there may be more contact between individual animals as they search for mates promoting aerosol spread of virus . Contact structure of a raccoon population can significantly impact disease transmission with Raccoon contact networks being shown to change depending on the season (breeding vs. non breeding); Rabies has been shown to spread quickly in raccoons when introduced during the breeding season.) (Reynolds, Hirsch, Gehrt, & Craft, 2015). Other potential influences of the breeding season and cases aside from contact may be the phycological strain of reproduction may leave animals more susceptible to the virus or as these cases are from animals found dead it could be that the increased movement from the breeding season leads to more being killed in other ways, such as on roads, and they happen to also be CDV positive at necropsy.

There as significant limitations to using this data set to draw conclusions about CDV cases in wild animals in Georgia. This data set comes from passive surveillance only, with it being reliant on dead animals being found and sent to SCWDS by DNR officers for necropsy. This leaves the data open to significant influence by reporting bias, as the distribution of DNR officers is not uniform across the state. Passive surveillance is also only showing part of the picture, with the results being heavily skewed towards symptomatic cases. Gray foxes and raccoons in Tennessee (Nov. 2013 – Aug. 2014) were infected frequently, but passive surveillance only captures animals showing clinical signs. Does not account for asymptomatic cases with 55% of asymptomatic animals tested being positive in this study (Pope, Miller, Riley, Anis, & Wilkes, 2016). There is also the difficulties associated with the size of the data set when it comes to trying to look at spatial and temporal trends together. Currently it is only possible to have meaningful numbers for analysis by looking at spatial trends using all the data, but obviously these cases are occuring over a very long period of time, the opposite is true for looking at temporal trends whereby only meanigful numbers can be gained by using cases over a huge area the size of Georgia.

Conclusions

The results from this analysis suggest that there are temporal and spatial patterns of CDV cases with the two most commonly infected wild carnivores in Georgia; Raccoons and Gray Foxes. Time series analysis and ARIMA model construction suggests that numbers of Raccoon cases can be predicted using data on the number of Gray Foxes casses frm the previous three months. There appears to be temporal trends in cases in both species, with cases more likely to occur during the breeding season. Spatially there tends to be clustering of cases of both species within the same areas, with cases appearing more likely to occur in area of medium human population density with fewer cases in very densely and sparsely populated areas. Ultimately, there is enough trends suggested from this passively coolected data which would support a worthwhile study, with comprehsive sampling of wild carnivores over time and space to try to elucidate spillover trendsbetween species, paricularly in suburban areas.

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